By immersing learners in a playful, interactive, and engaging experience, Educational Escape Rooms (EERs) have been found to enhance learners’ motivation, help them to develop 21st century skills, and improve knowledge acquisition. As research into EERs is still in a preliminary phase, no unified framework about how to design them has been established yet. Additionally, existing frameworks rarely validate the quality and efficacy of the frameworks themselves in terms of usability and usefulness. Therefore, the present paper proposes Room2Educ8, a learner-centred framework for EER design that follows Design Thinking principles. It provides detailed heuristics for empathising with learners, defining learning objectives and constraints, adding narrative, designing puzzles, briefing and debriefing participants, prototyping and playtesting, documenting the whole process, and evaluating the EER experience. A mixed-methods internal validation study based on Instructional Design model validation was conducted with 104 postgraduate students between 2018–2022 to assess the framework’s integrity and use. The study findings suggest that Room2Educ8 can be proposed as a valid tool for developing a wide range of EER types that cover a variety of topics. Its well-described and practical steps make it appropriate for educators regardless of a lack of prior experience in EER design.

Despite the educational potential of Facebook and Moodle, there are still unanswered questions about their impact on the student learning experience in a well-defined instructional design framework. This study aimed to compare the learning experiences of students who used Moodle (control group) and Facebook (experimental group), in terms of Community of Inquiry (CoI) model presence indicators, that is, cognitive, teaching, and social presence. Several learning activities for the development of learning environments were carried out by ninety-seven (n = 97) students who were enrolled in instructional media design courses in higher education. Findings from quantitative and qualitative analysis indicated that students using either Moodle or Facebook as their learning platform had similar perceptions of teaching and cognitive presence; however, Facebook users had a better social presence using the CoI model than their Moodle counterparts. Another point worth noting is that the experimental group’s female participants had better teaching presence, cognitive presence, and overall learning experience than their male peers.

Reflective learning is widely recognised as a highly effective approach to learning. It involves learners in a process wherein they reflect on their past experiences to improve their skills and knowledge. In recent years, there has been growing recognition of the capacity of games to facilitate experiential learning. Therefore, this research aimed to evaluate the effectiveness of integrating reflective design principles into digital game-based learning (GBL). The focus was on assessing the reliability and appropriateness of reflective game design, as well as learner perceptions. This study adopted a participatory design approach, ensuring the active involvement of the target audience across all extensive phases. The research consisted of three main phases. Firstly, reflective learning was integrated into game design to develop the Reflective Game Design (RGD) framework. This development was guided by insights gathered from participants through both a user survey (N = 101) and semi-structured interviews (N = 15). Subsequently, a GBL digital game was developed based on the RGD framework in co-design sessions (N = 6). Finally, a prototype evaluation (N = 56) was conducted to assess the feasibility and practicality of implementing reflective game design within digital GBL contexts. Overall, the RGD approach and the game prototype received positive feedback in terms of engagement, content clarity, the incorporation of reflective game elements, and player immersion. This study contributes to the literature by providing principles and guidelines for RGD, thus offering valuable insights for researchers, educators, and game designers looking to create effective educational games.

A comparative evaluation of applying algorithms is presented, based on Hidden Markov Models and Artificial Neural Networks, in order to create a corpus of chants through vocal music recognition. The sound signal sequences of singing performances were captured, a training dataset was created based on the extracted sound features of the captured sound signal sequences and finally, the music recognition system was trained using the mentioned algorithms. Finally, the music recognition was performed and a score of successfully recognized of hymn performances was calculated by utilizing the cross - validation statistical method Jackknife. The results of the evaluation revealed that HMM algorithm is more efficient than ANN in order to train a machine learning system for chanting recognition. The findings can be used to build and/or improve the performance of machine learning systems for monophonic singing recognition.